Fine-tuning
Also known as: Model customization, Transfer learning
Customizing a pre-trained AI model with your own data to make it better at specific tasks. Fine-tuning makes generic AI models sound like they work at your company.
Context
Fine-tuning makes generic AI models sound like they work at your company. A customer service chatbot fine-tuned on your actual support tickets will give better, more on-brand answers than a generic one. An email writer fine-tuned on your past campaigns will match your tone. Fine-tuning requires providing examples—usually hundreds or thousands—of the specific task you want the AI to master.
Examples
- 1Fine-tuning ChatGPT on your knowledge base for better customer support
- 2Training an AI writer on your blog posts to match your voice
- 3Customizing sentiment analysis for your industry's terminology